Bayesian inference in camera trapping studies for a class of spatial capture–recapture models

Royle, J. Andrew; Karanth, K. Ullas; Gopalaswamy, Arjun M.; Kumar, N. Samba

doi:10.1890/08-1481.1

Cited by 276 publications

(421 citation statements)

References 24 publications

Supporting

Mentioning

413

Contrasting

Order By: Relevance

“…SCR has become the standard method for obtaining such information for many species, and is now routinely used to estimate abundance of populations of conservation concern including species such as tigers (Royle et al 2009), grizzly bears (Efford andMowat 2014, Kendall et al 2016), wolverines (Magoun et al 2011, Box 1) and jaguars (Sollmann et al 2011). These and many other species are extremely difficult to capture and so non-invasive sampling combined with SCR methods are well suited to study these species.…”

Section: Resultsmentioning

confidence: 99%

Unifying population and landscape ecology with spatial capture–recapture

Royle¹,

Fuller

Sutherland³

2017

Ecography

Self Cite

126

172

View full text Add to dashboard Cite

Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio-temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population state and structure. Spatial capture-recapture (SCR) represents an individual-based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and they have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g. camera trapping, non-invasive DNA sampling). We describe ways in which SCR methods stand to advance the study of animal population ecology.

show abstract

Section: Resultsmentioning

confidence: 99%

Unifying population and landscape ecology with spatial capture–recapture

Royle¹,

Fuller

Sutherland³

2017

Ecography

Self Cite

126

172

View full text Add to dashboard Cite

show abstract

“…No lure was used and there was no evidence of animals being attracted to particular camera stations. It is likely that, as suggested by Royle et al (2009), the positive response was caused by a preferential use of certain trails by individuals within their territory. Overall it is believed that the spatially-explicit capture-recapture model will provide a more accurate result than simple capture-recapture models (J.A.…”

Section: Discussionmentioning

confidence: 97%

“…Funston et al, 2010) was used to convert spoor density to true density (t i =3.15x i +0.40 where t i is the observed spoor density and x i is the observed carnivore density). Camera survey data were analysed with Bayesian spatially explicit capture-recapture methods (Royle et al, 2009), using SPACECAP v. 1.0.5 (Gopalaswamy et al, 2012 in R. Each survey was analysed separately. SPACECAP requires three input files: a capture history, the UTM coordinates of the camera array, including information on which trap locations were active on each sampling occasion, and a file of UTM coordinates of potential home range centres.…”

Section: Methodsmentioning

confidence: 99%

The importance of farmland for the conservation of the brown hyaena Parahyaena brunnea

Kent

Hill

2013

Oryx

View full text Add to dashboard Cite

Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract The conservation of wide-ranging, territorial carnivores presents many challenges, not least the inadequacy of many protected areas in providing sufficient space to allow such species to maintain viable populations. As a result populations occurring outside protected areas may be of considerable importance for the conservation of some species, although the significance of these areas is poorly understood. Brown hyaenas Parahyaena brunnea are categorized as Near Threatened on the IUCN Red List and recent research suggests the species may be particularly vulnerable to habitat loss and the conversion of land to agriculture. Here we report on the population density and abundance of brown hyaenas in an area of commercial farmland in western Botswana. Mean brown hyaena density estimated from camera-trap surveys was 2.3 per 100 km 2 and from spoor surveys was 2.88 per 100 km 2 , which are comparable to estimates reported for protected areas. Estimated densities were higher on farms used for livestock production than on those used for game farming, suggesting that the species can tolerate land use change where reliable alternative food resources exist. Our results indicate that populations of brown hyaenas in non-protected areas comprise a significant proportion of the global population and that such areas may be of critical importance for their conservation.

show abstract

“…The Poisson distribution, f m (m i jk ) of Eq. (12) was proposed by Royle et al (2009) for modelling m i jk , and it is to date the only model that has been used, although overdispersed count models have been suggested. With this model, P(ω i |s i ) in Eq.…”

Section: Scr Detection and Capture Modelsmentioning

confidence: 99%

From distance sampling to spatial capture–recapture

Borchers

Marques

2017

AStA Adv Stat Anal

View full text Add to dashboard Cite

Distance sampling and capture-recapture are the two most widely used wildlife abundance estimation methods. capture-recapture methods have only recently incorporated models for spatial distribution and there is an increasing tendency for distance sampling methods to incorporated spatial models rather than to rely on partly design-based spatial inference. In this overview we show how spatial models are central to modern distance sampling and that spatial capture-recapture models arise as an extension of distance sampling methods. Depending on the type of data recorded, they can be viewed as particular kinds of hierarchical binary regression, Poisson regression, survival or time-to-event models, with individuals' locations as latent variables and a spatial model as the latent variable distribution. Incorporation of spatial models in these two methods provides new opportunities for drawing explicitly spatial inferences. Areas of likely future development include more sophisticated spatial and spatio-temporal modelling of individuals' locations and movements, new methods for integrating spatial capture-recapture and other kinds of ecological survey data, and methods for dealing with the recapture uncertainty that often arise when "capture" consists of detection by a remote device like a camera trap or microphone.

show abstract

Bayesian inference in camera trapping studies for a class of spatial capture–recapture models

Cited by 276 publications

References 24 publications

Unifying population and landscape ecology with spatial capture–recapture

Unifying population and landscape ecology with spatial capture–recapture

The importance of farmland for the conservation of the brown hyaena Parahyaena brunnea

From distance sampling to spatial capture–recapture

Contact Info

Product

Resources

About